A Dynamic Transcriptome Map of Different Tissue Microenvironment Cells Identified During Gastric Cancer Development Using Single-Cell RNA Sequencing

Gene expression profile of human placental villous pericytes in the first trimester - An analysis by single-cell RNA sequencing

Mesenchymal cells within theplacental villi play a crucial role in shaping the morphology of branching structures and driving the development of blood vessels. However, the markers and functions of placental villous pericytes (PVPs) as distinct subgroups of placental villous mesenchymal cells, remain unclear. Therefore, in this study, the markers and functions of PVPs were investigated. Single-cell sequencing data from the first-trimester placental villi was obtained and the Seurat tool was used to identify PVP markers. Gene Ontology (GO) analysis of specific genes was performed using the DAVID database. The Cellchat tool was employed to investigate the interaction signals between the PVPs and other cells. Expression of the PVP markers was confirmed using immunofluorescence. Presence of extracellular vesicles in the placental villous mesenchyme and PVPs was examined by transmission electron microscopy. Our findings revealed that renin (REN) and amphiregulin (AREG)-positive fibroblasts in the placental villi specifically expressed several classic pericyte markers. In the first trimester, certain conserved functions of pericytes were observed and they displayed tissue-specific functions such as in the integrin-mediated signaling pathway and extracellular exosomes. Moreover, the placental villous mesenchyme was found to be rich in extracellular vesicles. AREG is specifically transcribed in the first trimester PVPs, however, its protein was located in syncytiotrophoblasts. These insights contribute to a comprehensive understanding of early placental development and offer new therapeutic targets for placenta-derived pregnancy complications.

Characterization of tumor endothelial cells (TEC) in gastric cancer and development of a TEC-based risk signature using single-cell RNA-seq and bulk RNA-seq data

BACKGROUND

Tumor endothelial cells (TECs) are essential participants in tumorigenesis. This study is focused on elucidating the TEC traits in gastric cancer (GC) and constructing a prognostic risk model to predict the clinical outcome of GC patients.

METHODS

Single-cell RNA sequencing (scRNA-seq) data were obtained from the GEO database. Using specific markers, the Seurat R package aided in processing scRNA-seq data and identifying TEC clusters. Based on TEC cluster-associated genes identified by Pearson correlation analysis, TEC-related prognostic genes were screened by lasso-Cox regression analysis, thereby constructing a risk signature. A nomogram was created by combining the risk signature with clinicopathological features.

RESULTS

Based on the scRNA-seq data, 5 TEC clusters were discovered in GC, with 3 of them showing prognostic associations in GC. A total of 163 genes were pinpointed among 3302 DEGs as significantly linked to TEC clusters, leading to the formulation of a risk signature comprising 8 genes. Furthermore, there was a notable correlation between the risk signature and the immune cell infiltration. Multivariate analysis findings indicated that the risk signature served as an independent prognostic factor for GC. Moreover, its efficacy in forecasting immune response was validated.

CONCLUSION

TEC-based risk model is highly effective in predicting the survival outcomes of GC patients and can forecast the immune response. Targeting TECs may significantly inhibit tumor progression and enhance the efficacy of immunotherapy.

Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research

Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.

Highlights of how single-cell analyses are illuminating differentiation and disease in the gastric corpus

Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful technique to identify novel cell markers, developmental trajectories, and transcriptional changes during cell differentiation and disease onset and progression. In this review, we highlight recent scRNA-seq studies of the gastric corpus in both human and murine systems that have provided insight into gastric organogenesis, identified novel markers for the various gastric lineages during development and in adults, and revealed transcriptional changes during regeneration and tumorigenesis. Overall, by elucidating transcriptional states and fluctuations at the cellular level in healthy and disease contexts, scRNA-seq may lead to better, more personalized clinical treatments for disease progression.

Glycolysis regulation in tumor-associated macrophages: Its role in tumor development and cancer treatment

Tumor-associated macrophages constitute the main cell population in the tumor microenvironment and play a crucial role in regulating the microenvironment composition. Emerging evidence has revealed that the metabolic profile determines the tumor-associated macrophage phenotype. Tumor-associated macrophage function is highly dependent on glucose metabolism, with glycolysis being the major metabolic pathway. Recent reports have demonstrated diversity in glucose flux of tumor-associated macrophages and complex substance communication with cancer cells. However, how the glucose flux in tumor-associated macrophages connects with glycolysis to influence tumor progression and the tumor microenvironment is still obscure. Moreover, while the development of single-cell sequencing technology allows a clearer and more accurate classification of tumor-associated macrophages, the metabolic profiles of tumor-associated macrophages from the perspective of single-cell omics has not been well summarized. Here, we review the current state of knowledge on glucose metabolism in tumor-associated macrophages and summarize the metabolic profiles of different tumor-associated macrophage subtypes from the perspective of single-cell omics. Additionally, we describe the current strategies targeting glycolysis in tumor-associated macrophages for cancer therapy.

Metabolic regulation of tumor-associated macrophage heterogeneity: insights into the tumor microenvironment and immunotherapeutic opportunities

Tumor-associated macrophages (TAMs) are a heterogeneous population that play diverse functions in tumors. Their identity is determined not only by intrinsic factors, such as origins and transcription factors, but also by external signals from the tumor microenvironment (TME), such as inflammatory signals and metabolic reprogramming. Metabolic reprogramming has rendered TAM to exhibit a spectrum of activities ranging from pro-tumorigenic to anti-tumorigenic, closely associated with tumor progression and clinical prognosis. This review implicates the diversity of TAM phenotypes and functions, how this heterogeneity has been re-evaluated with the advent of single-cell technologies, and the impact of TME metabolic reprogramming on TAMs. We also review current therapies targeting TAM metabolism and offer new insights for TAM-dependent anti-tumor immunotherapy by focusing on the critical role of different metabolic programs in TAMs.

The CAR macrophage cells, a novel generation of chimeric antigen-based approach against solid tumors

Today, adoptive cell therapy has many successes in cancer therapy, and this subject is brilliant in using chimeric antigen receptor T cells. The CAR T cell therapy, with its FDA-approved drugs, could treat several types of hematological malignancies and thus be very attractive for treating solid cancer. Unfortunately, the CAR T cell cannot be very functional in solid cancers due to its unique features. This treatment method has several harmful adverse effects that limit their applications, so novel treatments must use new cells like NK cells, NKT cells, and macrophage cells. Among these cells, the CAR macrophage cells, due to their brilliant innate features, are more attractive for solid tumor therapy and seem to be a better candidate for the prior treatment methods. The CAR macrophage cells have vital roles in the tumor microenvironment and, with their direct effect, can eliminate tumor cells efficiently. In addition, the CAR macrophage cells, due to being a part of the innate immune system, attended the tumor sites. With the high infiltration, their therapy modulations are more effective. This review investigates the last achievements in CAR-macrophage cells and the future of this immunotherapy treatment method.

Identification of stromal cell proportion-related genes in the breast cancer tumor microenvironment using CorDelSFS feature selection: implications for tumor progression and prognosis

Background: The tumor microenvironment (TME) of breast cancer (BRCA) is a complex and dynamic micro-ecosystem that influences BRCA occurrence, progression, and prognosis through its cellular and molecular components. However, as the tumor progresses, the dynamic changes of stromal and immune cells in TME become unclear. Objective: The aim of this study was to identify differentially co-expressed genes (DCGs) associated with the proportion of stromal cells in TME of BRCA, to explore the patterns of cell proportion changes, and ultimately, their impact on prognosis. Methods: A new heuristic feature selection strategy (CorDelSFS) was combined with differential co-expression analysis to identify TME-key DCGs. The expression pattern and co-expression network of TME-key DCGs were analyzed across different TMEs. A prognostic model was constructed using six TME-key DCGs, and the correlation between the risk score and the proportion of stromal cells and immune cells in TME was evaluated. Results: TME-key DCGs mimicked the dynamic trend of BRCA TME and formed cell type-specific subnetworks. The IG gene-related subnetwork, plasmablast-specific expression, played a vital role in the BRCA TME through its adaptive immune function and tumor progression inhibition. The prognostic model showed that the risk score was significantly correlated with the proportion of stromal cells and immune cells in TME, and low-risk patients had stronger adaptive immune function. IGKV1D-39 was identified as a novel BRCA prognostic marker specifically expressed in plasmablasts and involved in adaptive immune responses. Conclusions: This study explores the role of proportionate-related genes in the tumor microenvironment using a machine learning approach and provides new insights for discovering the key biological processes in tumor progression and clinical prognosis.

Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics studies of tumour endothelial cells (TECs) have provided new mechanistic insight. Here, we overview the heterogeneity of human TECs of all tumour types studied to date, at the single-cell level. Notably, most human tumour types contain varying numbers but only a small population of angiogenic TECs, the presumed targets of AATs, possibly contributing to the limited efficacy of and resistance to AATs. In general, TECs are heterogeneous within and across all tumour types, but comparing TEC phenotypes across tumours is currently challenging, owing to the lack of a uniform nomenclature for endothelial cells and consistent single-cell analysis protocols, urgently raising the need for a more consistent approach. Nonetheless, across most tumour types, universal TEC markers (ACKR1, PLVAP and IGFBP3) can be identified. Besides angiogenesis, biological processes such as immunomodulation and extracellular matrix organization are among the most commonly predicted enriched signatures of TECs across different tumour types. Although angiogenesis and extracellular matrix targets have been considered for AAT (without the hoped success), the immunomodulatory properties of TECs have not been fully considered as a novel anticancer therapeutic approach. Therefore, we also discuss progress, limitations, solutions and novel targets for AAT development.

Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects

Gastric cancer is one of the most serious malignant tumor and threatens the health of people worldwide. Its heterogeneity leaves many clinical problems unsolved. To treat it effectively, we need to explore its heterogeneity. Single-cell transcriptome sequencing, or single-cell RNA sequencing (scRNA-seq), reveals the complex biological composition and molecular characteristics of gastric cancer at the level of individual cells, which provides a new perspective for understanding the heterogeneity of gastric cancer. In this review, we first introduce the current procedure of scRNA-seq, and discuss the advantages and limitations of scRNA-seq. We then elaborate on the research carried out with scRNA-seq in gastric cancer in recent years, and describe how it reveals cell heterogeneity, the tumor microenvironment, oncogenesis and metastasis, as well as drug response in to gastric cancer, to facilitate early diagnosis, individualized therapy, and prognosis evaluation.

Heterogeneity of glioblastoma stem cells in the context of the immune microenvironment and geospatial organization

Glioblastoma (GBM) is an extremely aggressive and incurable primary brain tumor with a 10-year survival of just 0.71%. Cancer stem cells (CSCs) are thought to seed GBM's inevitable recurrence by evading standard of care treatment, which combines surgical resection, radiotherapy, and chemotherapy, contributing to this grim prognosis. Effective targeting of CSCs could result in insights into GBM treatment resistance and development of novel treatment paradigms. There is a major ongoing effort to characterize CSCs, understand their interactions with the tumor microenvironment, and identify ways to eliminate them. This review discusses the diversity of CSC lineages present in GBM and how this glioma stem cell (GSC) mosaicism drives global intratumoral heterogeneity constituted by complex and spatially distinct local microenvironments. We review how a tumor's diverse CSC populations orchestrate and interact with the environment, especially the immune landscape. We also discuss how to map this intricate GBM ecosystem through the lens of metabolism and immunology to find vulnerabilities and new ways to disrupt the equilibrium of the system to achieve improved disease outcome.

Angiogenesis goes computational - The future way forward to discover new angiogenic targets?

Multi-omics technologies are being increasingly utilized in angiogenesis research. Yet, computational methods have not been widely used for angiogenic target discovery and prioritization in this field, partly because (wet-lab) vascular biologists are insufficiently familiar with computational biology tools and the opportunities they may offer. With this review, written for vascular biologists who lack expertise in computational methods, we aspire to break boundaries between both fields and to illustrate the potential of these tools for future angiogenic target discovery. We provide a comprehensive survey of currently available computational approaches that may be useful in prioritizing candidate genes, predicting associated mechanisms, and identifying their specificity to endothelial cell subtypes. We specifically highlight tools that use flexible, machine learning frameworks for large-scale data integration and gene prioritization. For each purpose-oriented category of tools, we describe underlying conceptual principles, highlight interesting applications and discuss limitations. Finally, we will discuss challenges and recommend some guidelines which can help to optimize the process of accurate target discovery.

scRNA-seq of gastric tumor shows complex intercellular interaction with an alternative T cell exhaustion trajectory

The tumor microenvironment (TME) in gastric cancer (GC) has been shown to be important for tumor control but the specific characteristics for GC are not fully appreciated. We generated an atlas of 166,533 cells from 10 GC patients with matched paratumor tissues and blood. Our results show tumor-associated stromal cells (TASCs) have upregulated activity of Wnt signaling and angiogenesis, and are negatively correlated with survival. Tumor-associated macrophages and LAMP3⁺ DCs are involved in mediating T cell activity and form intercellular interaction hubs with TASCs. Clonotype and trajectory analysis demonstrates that Tc17 (IL-17⁺CD8⁺ T cells) originate from tissue-resident memory T cells and can subsequently differentiate into exhausted T cells, suggesting an alternative pathway for T cell exhaustion. Our results indicate that IL17⁺ cells may promote tumor progression through IL17, IL22, and IL26 signaling, highlighting the possibility of targeting IL17⁺ cells and associated signaling pathways as a therapeutic strategy to treat GC.

Gastric cancer can vary in tumour stage and immune cell involvement. Here the authors compare gene expression in immune cell types from the blood and the tumour site from GC patients using single cell and TCR sequencing and show that IL17⁺CD8⁺ T cells have a phenotype related to that seen with exhausted cells.

Macrophage diversity in cancer revisited in the era of single-cell omics

Tumor-associated macrophages (TAMs) have multiple potent functions in cancer and, thus, represent important therapeutic targets. These diverse functions highlight the heterogenous nature of TAMs. Recent single cell omics technologies have significantly advanced our understanding of the molecular diversity of TAMs. However, a unifying nomenclature of TAM diversity and annotation of their molecular signatures is lacking. Here, we review recent major studies of single cell transcriptome, epigenome, metabolome, and spatial omics of cancer with a specific focus on TAMs. We also propose a consensus model of TAM diversity and present avenues for future research.

Discovering Immune-Mediated Mechanisms of Gastric Carcinogenesis Through Single-Cell RNA Sequencing

Single-cell RNA sequencing (scRNAseq) technology is still relatively new in the field of gastric cancer immunology but gaining significant traction. This technology now provides unprecedented insights into the intratumoral and intertumoral heterogeneities at the immunological, cellular, and molecular levels. Within the last few years, a volume of publications reported the usefulness of scRNAseq technology in identifying thus far elusive immunological mechanisms that may promote and impede gastric cancer development. These studies analyzed datasets generated from primary human gastric cancer tissues, metastatic ascites fluid from gastric cancer patients, and laboratory-generated data from in vitro and in vivo models of gastric diseases. In this review, we overview the exciting findings from scRNAseq datasets that uncovered the role of critical immune cells, including T cells, B cells, myeloid cells, mast cells, ILC2s, and other inflammatory stromal cells, like fibroblasts and endothelial cells. In addition, we also provide a synopsis of the initial scRNAseq findings on the interesting epithelial cell responses to inflammation. In summary, these new studies have implicated roles for T and B cells and subsets like NKT cells in tumor development and progression. The current studies identified diverse subsets of macrophages and mast cells in the tumor microenvironment, however, additional studies to determine their roles in promoting cancer growth are needed. Some groups specifically focus on the less prevalent ILC2 cell type that may contribute to early cancer development. ScRNAseq analysis also reveals that stromal cells, e.g., fibroblasts and endothelial cells, regulate inflammation and promote metastasis, making them key targets for future investigations. While evaluating the outcomes, we also highlight the gaps in the current findings and provide an assessment of what this technology holds for gastric cancer research in the coming years. With scRNAseq technology expanding rapidly, we stress the need for periodic review of the findings and assess the available scRNAseq analytical tools to guide future work on immunological mechanisms of gastric carcinogenesis.  

Mapping and Validation of scRNA-Seq-Derived Cell-Cell Communication Networks in the Tumor Microenvironment

Recent advances in single-cell technologies, particularly single-cell RNA-sequencing (scRNA-seq), have permitted high throughput transcriptional profiling of a wide variety of biological systems. As scRNA-seq supports inference of cell-cell communication, this technology has and continues to anchor groundbreaking studies into the efficacy and mechanism of novel immunotherapies for cancer treatment. In this review, we will highlight methods developed to infer inter- and intracellular signaling from scRNA-seq and discuss how they have contributed to studies of immunotherapeutic intervention in the tumor microenvironment (TME). However, a central challenge remains in validating the hypothesized cell-cell interactions. Therefore, this review will also cover strategies for integration of these scRNA-seq-derived interaction networks with existing experimental and computational approaches. Integration of these networks with imaging, protein secretion measurements, and network analysis and mathematical modeling tools addresses challenges that remain with scRNA-seq to enhance studies of immunosuppressive and immunotherapy-altered signaling in the TME.